Obianuju Okeke Data-verified

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

UA Little Rock

Last publication 2024 Last refreshed 2026-05-16

unknown

3 h-index 5 pubs 36 cited

Research Areas

Links

ORCID Research Group

OverviewAI-generated summary

Obianuju Okeke's research investigates bias and fairness in artificial intelligence, particularly within recommendation systems like YouTube. Her work examines how these algorithms can be influenced by factors such as emotion, morality, and network dynamics, impacting geopolitical discourse and the emergence of collective identity. Okeke also explores the application of parallel processing for efficient transcript generation in multimedia environments. She has collaborated with researchers including Billy Spann, Mert Can Çakmak, Nitin Agarwal, and Ugochukwu Onyepunuka, all from the University of Arkansas at Little Rock, on multiple shared publications. Her scholarly output includes 5 publications with an h-index of 3 and 36 total citations.

Metrics

h-index: 3
Publications: 5
Citations: 36

Selected Publications

Evaluating Bias and Fairness in AI: An Analysis of YouTube’s Recommendation Algorithm and its Impact on Geopolitical Discourse (2024)

DOI OpenAlex
Investigating Bias in YouTube Recommendations: Emotion, Morality, and Network Dynamics in China-Uyghur Content (2024)

10 citations DOI OpenAlex
Analyzing Bias in Recommender Systems: A Comprehensive Evaluation of YouTube's Recommendation Algorithm (2023)

11 citations DOI OpenAlex
Adopting Parallel Processing for Rapid Generation of Transcripts in Multimedia-rich Online Information Environment (2023)

14 citations DOI OpenAlex
Evaluating the Emergence of Collective Identity using Socio-Computational Techniques (2023)

1 citation DOI OpenAlex